R E S E A R C H
Open Access
Extremes of weight centile are associated with
increased risk of mortality in pediatric intensive
care
Andrew Numa
1,2*
, John McAweeney
1
, Gary Williams
1,2
, John Awad
1,2
and Hari Ravindranathan
1,2
Abstract
Introduction: Although numerous studies have linked extremes of weight with poor outcome in adult intensive
care patients, the effect of weight on intensive care outcome has not previously been reported in the pediatric
population. The aim of this study was to investigate the relationship between admission weight centile and risk-
adjusted mortality in pediatric intensive care patients.
Methods: Data were collected on 6337 consecutively admitted patients over an 8.5 year period in a 15 bed
pediatric intensive care unit (ICU) located in a university-affiliated tertiary referral children
’s hospital. A weight
centile variable was entered into a multivariate logistic regression model that included all other pediatric index of
mortality (PIM-2) variables, in order to determine whether weight centile was an independent risk factor for
mortality.
Results: Weight centile was associated with mortality in both univariate and multivariate analysis, with the lowest
mortality being associated with weights on the 75
th
centile and increasing symmetrically around this nadir. A
transformed weight centile variable (absolute value of weight centile-75) was independently associated with
mortality (odds ratio 1.02, P = 0.000) when entered into a multivariate logistic regression model that included the
PIM-2 variables.
Conclusions: In this single-center cohort, weight centile was an independent risk factor for mortality in the ICU,
with mortality increasing for patients at either end of the weight spectrum. These observations suggest that the
accuracy of mortality prediction algorithms may be improved by inclusion of weight centile in the models. A
prospective multicenter study should be undertaken to confirm our findings.
Introduction
Nutritional status has significant effects on morbidity
and mortality in the general population. Obesity is well
recognized as a risk factor for many disorders of adult
life, including diabetes, hypertension, coronary vascular
disease, osteoarthritis, depression, and some malignan-
cies, and significantly increases all-cause mortality [1-4].
At the other end of the spectrum, nutritional deficiency
is a major contributor to infant and child mortality
throughout the world [5,6], and body mass index (BMI)
of less than 18.5 kg/m
2
has been associated with minor
increases in all-cause mortality in adults [1].
Studies in adult intensive care patients have demon-
strated a variable relationship between BMI and mortal-
ity. A number of studies have failed to demonstrate any
impact of body mass on intensive care outcome [7-11],
whereas others have demonstrated an association
between obesity and increased risk-adjusted mortality
[12-14]. A considerable body of evidence suggests that
underweight adult intensive care patients are at the
greatest risk for mortality, and risk-adjusted odds ratios
(ORs) for death of 1.16 to 1.63 compared with patients
of normal weight have been reported [15-17]. No studies
have addressed the impact of body weight on outcome
in the pediatric intensive care unit (PICU), although
Larsen and colleagues [18] noted that low weight (but
not age) was an independent risk factor for mortality in
children undergoing cardiac surgery. We undertook this
* Correspondence: a.numa@unsw.edu.au
1
Intensive Care Unit, Sydney Children
’s Hospital, High Street, Randwick 2031,
Australia
Full list of author information is available at the end of the article
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© 2011 Numa et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons
Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in
any medium, provided the original work is properly cited.
study to explore the relationship between weight centile
and risk-adjusted mortality in PICU patients.
Materials and methods
Sydney Children
’s Hospital is a university-affiliated
pediatric tertiary referral center with all medical and
surgical subspecialties represented. The ICU annually
admits approximately 850 patients who range in age
from birth to 16 years and is one of three tertiary pedia-
tric centers in the state of New South Wales, serving a
total population of approximately 6.77 million, including
1.32 million children who are 14 years old or younger.
A separate neonatal ICU (NICU) on campus provides
care for premature infants; however, infants born with
complex surgical conditions (for example, congenital
diaphragmatic hernia and structural heart disease) are
generally managed in the PICU rather than the campus
NICU. The ICU offers a full range of supportive thera-
pies, including inhaled nitric oxide, high-frequency ven-
tilation, hemofiltration, and extra-corporeal membrane
oxygenation.
All patients admitted to the ICU between 1 January
2002 and 30 June 2010 were eligible for inclusion in this
study. Body weight, obtained from recent health records,
parental knowledge, or direct measurement, was
recorded on admission to the ICU. PIM-2 (Pediatric
Index of Mortality version 2) variables [19], along with
body weight, were prospectively recorded in all patients.
Weight-for-age
z-scores were calculated from data from
the Centers for Disease Control and Prevention [20] and
converted to centiles. For preterm infants less than 2
years old at admission, corrected age was used in prefer-
ence to chronological age. If corrected age was less than
term, preterm growth charts were used to calculate
weight centile [21].
The relationship between weight centile and mortality
was explored by using Copas
p by x plots [22], and sta-
tistical significance was confirmed by using the Mann-
Whitney
U test. Univariate and multivariate logistic
regression was performed to explore the relationship
between PIM-2 variables together with weight centile
and mortality. Standardized mortality rates were calcu-
lated by using PIM-2 coefficients [19], and statistical sig-
nificance was determined by Poisson analysis; binomial
proportions were compared by using standard equations
[23]. Comparison of areas under receiver operating
characteristic (ROC) curves was carried out by using
likelihood ratio testing [24]. Statistics were analyzed by
using SPSS 18.0.2 (IBM Corporation, Armonk, NY,
USA) and GraphPad Prism 5.0 (GraphPad Software,
Inc., La Jolla, CA, USA). The study was approved by the
ethics committee of the South Eastern Sydney and Illa-
warra Health Service, and informed consent was not
required for this analysis of data, which are routinely
collected on all ICU patients.
Results
Six thousand three hundred thirty-seven patients were
admitted to the ICU during the study period. Of these,
16 had no weight recorded and 5 had a history of pre-
maturity with no gestational age recorded; these patients
(
n = 21) were excluded from further analysis. There
were 203 deaths in the 6,316 remaining patients, a mor-
tality of 3.2%. The PIM-2-predicted mortality was 226.2,
giving a standardized mortality rate of 0.897, which is
significantly better than predicted (
P = 0.008).
Patients at the extremes of the weight spectrum were
over-represented numerically (Figure 1). For example,
21.5% of patients had weights not above the 3rd centile
and 5.7% had weights on at least the 97th centile com-
pared with the expected 3% in each group if the popu-
lation was distributed normally (
P < 0.001). The
relationship between weight centile and mortality was
symmetrical around a nadir at the 75th centile (Figure
2), and mortality at the lower end of the weight spec-
trum was more than double that of patients at the 75th
centile nadir. Weight centile was thus transformed
before inclusion in the multivariate regression by using
the absolute value of weight centile minus 75 (that is, a
patient with a weight on the 5th centile would have a
transformed value of 70 used as the weight term in the
regression, and a patient with a weight on the 85th
centile would have a transformed value of 10). This
transformed weight variable was then entered into a
multivariate logistic regression model that included the
PIM-2 variables. All PIM-2 variables, with the excep-
tion of elective admission (
P = 0.486) and bypass (P =
0.069) status, were statistically significant in the model.
As there was a very high correlation in our cohort
between the
‘elective admission’ and ‘recovery post-
Figure 1 Distribution of patients by weight centile.
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procedure
’ categories, with only 283 (11.8%) of 2,402
elective admissions not being admitted from the recov-
ery room, it is not surprising that elective admission
status was not an independent predictor in a model
that included both variables (each was significant in
univariate analysis). Similarly, only 407 patients (6.4%)
were admitted following cardiopulmonary bypass,
and this variable just failed to achieve statistical
significance.
The transformed weight centile variable was signifi-
cant in univariate and multivariate analyses (OR for
death of 1.02;
P = 0.000 in multivariate analysis). Elimi-
nating elective status and bypass status from the regres-
sion model did not significantly change the ORs or
P
values for the other variables, including weight category
(OR for the transformed weight variable in the model
without elective and bypass status included = 1.02;
P =
0.000). Exclusion of premature infants from the analysis
did not substantially alter the findings (data not shown).
ORs for PIM-2 variables and the weight variable are
shown in Table 1. Including the weight variable in the
PIM-2 model increased the area under the ROC curve
from 0.876 (95% confidence interval 0.851 to 0.900) to
0.887 (0.864 to 0.909) (Figure 3). This increase in area
was statistically significant (
P = 0.0002).
Chromosomal or syndromal disorders or both were
present in 499 of 6,317 patients (7.9%) and were more
common in patients with lower weight centiles (
P <
0.001). Thirteen point eight percent of patients with
weights less than the 10th centile had a chromosomal or
syndromal disorder (or both) in comparison with only
2.6% of patients with weights greater than the 90th cen-
tile. However, there was no link between mortality and
presence of either a chromosomal or syndromal disor-
der; mortality in patients with and without such disor-
ders was 3.2% in each group.
Discussion
Mortality prediction scores in the PICU are important
tools for benchmarking unit performance. Neither of the
two most used predictive scores in pediatrics, the PIM-2
and the Pediatric Risk of Mortality (PRISM III), includes
weight centile as a variable [19,25]. Weight (not weight
centile) was examined during the development of PIM
Figure 2 Mortality versus weight centile. Distance-weighted least
squares plot is shown.
Table 1 Odds ratios for PIM-2 variables and weight
centile
PIM-2
OR
These data OR (95%
CI)
P
value
Pupils fixed to light
21.74
51.82 (18.82 to 136.32)
0.000
High-risk diagnosis
5.38
4.87 (3.31 to 7.19)
0.000
Mechanical ventilation
3.80
2.04 (1.38 to 2.99)
0.000
Bypass
2.12
1.79 (0.94 to 3.38)
0.069
100 × FiO
2
/PaO
2
1.34
1.35 (1.08 to 1.70)
0.006
Absolute base excess
1.11
1.05 (1.02 to 1.08)
0.000
Absolute (SBP - 120)
1.01
1.02 (1.01 to 1.03)
0.000
Absolute (weight centile -
75)
-
1.02 (1.01 to 1.02)
0.000
Elective admission
0.40
0.79 (0.39 to 1.56)
0.486
Recovery after procedure
0.36
0.17 (0.08 to 0.36)
0.000
Low-risk diagnosis
0.21
0.14 (0.06 to 0.35)
0.001
Constant
-4.88
-5.06 (-4.52 to -5.59)
0.000
CI, confidence interval; FiO
2
/PaO
2
, fraction of inspired oxygen/arterial partial
pressure of oxygen; OR, odds ratio; PIM-2, Pediatric Index of Mortality version
2; SBP, systolic blood pressure.
Figure 3 Comparison of receiver operating characteristic
curves for PIM-2 variables with (green curve) and without
(blue curve) the weight variable included in the model. PIM-2,
Pediatric Index of Mortality version 2.
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but was not significant on univariate testing and was
removed from the model [26].
Our data demonstrate that weight is an independent
risk factor for outcome, with an OR that is similar to
that of systolic blood pressure (OR 1.02); that is, a one
percentile change in admission weight has a mortality
risk effect similar to that of a 1 mm Hg change in systo-
lic blood pressure.
Nutritional deficiency is a major contributor to infant
and child mortality throughout the world [5,6] and is
directly responsible for approximately 300,000 childhood
deaths per year [27]. It is entirely plausible that nutri-
tional deficiency also increases the risk of mortality in
an intensive care population. Protein-energy malnutri-
tion has wide-ranging deleterious effects on human phy-
siology and these effects include cardiac, renal, and
hepatic function and humoral and cellular immunity
[27-29]. Other authors have noted associations between
nutritional deficiency and the development of multior-
gan failure [30,31] and mortality risk [32,33]. When
observed, excess mortality among overweight adult
intensive care patients has usually been attributed to
respiratory and cardiovascular dysfunction [12-14] but
these are less likely to be important issues in our popu-
lation. Several groups have reported an increased risk of
mortality in obese children with specific disorders,
including leukemia and end-stage renal disease [34-36].
Unfortunately, we did not have sufficient data to exam-
ine cause of mortality in this cohort of patients.
The value of a predictive score lies in its accuracy.
The existence of variables that can substantially affect
patient mortality but that are not included in widely
used predictive scores makes accurate comparison of
standardized mortality rates difficult. Several authors
have noted poor performance of discriminatory scores
when applied to non-Western populations [37-40] and
it is likely that nutritional status may be at least partly
responsible for this observation. Thukral and colleagues
[40] noted higher standardized mortality rates (calcu-
lated by both PIM-2 and PRISM) in children who had
severe malnutrition and who were admitted to an Indian
PICU. Our data suggest that any PICU with a relatively
large proportion of low-weight-centile patients will have
an inappropriately high standardized mortality rate
when current PIM or PRISM models are used.
Analysis of our patient population revealed excessive
numbers of patients with very low and very high weight
centiles. Patients with weight
≤3rd centile were numeri-
cally over-represented by a factor of 7 compared with
the expected number, and patients with weight
≥97th
centile were over-represented by a factor of 2. Pollack
and colleagues [41] noted a similarly high percentage
(18%) of chronically malnourished children in a PICU
population. Our data indicate that low weight centile
may represent a risk factor for ICU admission and also
an independent risk for mortality after admission to the
ICU. Many acute and chronic illnesses are associated
with weight loss, and the over-representation of low-
weight patients in the ICU population is biologically
plausible and not unexpected. An association between
low socioeconomic class and increased risk of intensive
care admission has also been reported [42] and this may
also contribute to increasing the proportion of patients
with low weight centile in the ICU. The apparent over-
representation at the other extreme of the centile range
may reflect merely the increasing incidence of obesity in
the community. In 2007-2008, 11.9% of American chil-
dren from 2 to 19 years of age had a BMI above the
97th centile [43], while a recent study of inpatients
(excluding intensive care patients) in an Australian ter-
tiary referral children
’s hospital demonstrated that 11%
of hospital inpatients more than 12 months old had a
BMI on at least the 97th centile when measured accord-
ing to the same growth parameters used for this study
[44]. The same study demonstrated that only 6% of hos-
pitalized inpatients were underweight (as defined by a
weight-for-age
z-score of less than -2.0).
One potential weakness of our study is that we did
not directly measure weight in the majority of the chil-
dren admitted to the ICU but instead relied on recorded
hospital admission weights (most patients admitted to
the non-ICU wards have weight measured on admis-
sion), parental knowledge, and infant health records. We
believe that the majority of weight measurements were
accurate, and any errors arising from this methodology
are likely to be random rather than systematic. Random
(as opposed to systematic) errors in study populations
are largely overcome by enrolling sufficient numbers of
patients [45]. Thus, the presence of random error will
increase the probability of a type II statistical error (fail-
ing to detect significant associations) but does not inva-
lidate a statistically significant result; we therefore
believe that our findings are likely to be correct.
Furthermore, measured admission weight on arrival in
the ICU will be affected by the patient
’s hydration sta-
tus, which will commonly vary over at least a 10% (that
is, ±5%) range. It has been suggested that excessive
volume resuscitation in critically ill adult patients before
admission to the ICU might mask the relationship
between weight and mortality by increasing mortality
risk in patients categorized as
‘overweight’ (when in rea-
lity these patients are merely overhydrated) [46]. Our
use of recent weights obtained in a period of good
health from infant health records and other sources is
likely to represent the true nutritional status of the
patient. Nevertheless, a prospective study including
accurate weight measurement on admission to the ICU
should be performed before weight centile can be
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considered for inclusion in PIM or PRISM scores. Simi-
larly, we did not measure height centile in our patients.
It is likely that some patients in our study had low or
high weight centiles that were accompanied by a com-
parably low or high height centile; that is, they were
simply small or tall rather than nutritionally deficient or
overweight. However, the number of proportionally
small or tall patients is unlikely to exceed the normal
population frequency; that is, we would expect 3% of
our patients to fall into the lowest and highest 3 centiles
at either end of the spectrum, not the 21.5% and 5.7%
we observed. An association was observed between low
weight centiles and the presence of chromosomal or
syndromal disorders or both; however, the mortality of
patients with these disorders was not different from the
mortality of the population as a whole, suggesting that
while such disorders are often associated with low
weight centile, the presence of these disorders is not
responsible for the increased mortality risk.
Conclusions
Admission weights at the extremes of the centile range
(low and high) are associated with an increased risk of
mortality in the PICU, and patients with weights at the
extremes of the centile range appear to be numerically
over-represented in the ICU, although for overweight
patients this may reflect simply the increasing incidence
of obesity in the community. Given that our data sug-
gest that inclusion of weight centile has the potential to
improve the accuracy of mortality prediction (particu-
larly in populations in which malnutrition may be more
prevalent), a multicenter prospective study of this vari-
able should be undertaken.
Key messages
• Weight centile is an independent risk factor for
mortality in patients admitted to pediatric intensive
care; the lowest mortality occurs in patients with
weights at the 75th centiles, and mortality increases
as patient weights move away from the 75th centile
toward either end of the weight spectrum.
• Weight centile should be considered for inclusion
as a variable in mortality prediction models.
Abbreviations
BMI: body mass index; ICU: intensive care unit; NICU: neonatal intensive care
unit; OR: odds ratio; PICU: pediatric intensive care unit; PIM-2: Pediatric Index
of Mortality version 2; PRISM: Pediatric Risk of Mortality; ROC: receiver
operating characteristic.
Acknowledgements
JM was supported by a grant from Sell & Parker Pty Ltd. (Banksmeadow,
NSW, Australia).
Author details
1
Intensive Care Unit, Sydney Children
’s Hospital, High Street, Randwick 2031,
Australia.
2
University of New South Wales, Anzac Parade, Kensington 2033,
Australia.
Authors
’ contributions
AN conceived of the study, analyzed the data, and drafted the manuscript.
JM, GW, JA, and HR contributed equally to refining the study design, data
collection, and manuscript revisions. All authors read and approved the final
manuscript.
Competing interests
The authors declare that they have no competing interests.
Received: 17 May 2010 Revised: 27 August 2010
Accepted: 31 March 2011 Published: 31 March 2011
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doi:10.1186/cc10127
Cite this article as: Numa et al.: Extremes of weight centile are
associated with increased risk of mortality in pediatric intensive care.
Critical Care 2011 15:R106.
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Numa
et al. Critical Care 2011, 15:R106
http://ccforum.com/content/15/2/R106
Page 6 of 6
Document Outline - Abstract
- Introduction
- Methods
- Results
- Conclusions
- Introduction
- Materials and methods
- Results
- Discussion
- Conclusions
- Key messages
- Acknowledgements
- Author details
- Authors' contributions
- Competing interests
- References
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